Data Visualization Means Business Intelligence

Data Visualization Means Business Intelligence

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By, Yuvraj Naidoo, IT Manager

Many companies work in industries that consume such high volume of structure and unstructured data that it qualifies as Big Data. Business owners and managers share a common pain point on how to harness the Big Data their businesses consume in a way to decipher historic trends, seasonal fluctuations, and predict future events that are not obvious in their daily metrics.

Despite accumulating massive amounts of data, companies typically only use the metrics required to conduct their daily transactions: loss runs, daily production, miles driven, weight, errors, hours, throughput, etc. Other times, managers may genuinely believe they understand their company’s trends because they have the data in front of them, or perhaps they rely on intuition, or anecdotal evidence.

Recently, Vantage Agora installed OX Zion, our proprietary Business Operating Solution, at a client to begin offering data visualization of their employees’ daily production. By marrying OX Zion to the company’s production platform, we could take individual data sets and automatically generate on-demand charts and graphs that offered the client a new look at the data. Rather than simply looking at data in a spreadsheet OX Zion converts the data into overall productivity, productivity by department, by employee, by day, by hour and create trends for each data point.

EXAMPLE 1

What was immediately visible was the daily production had a predictable cycle of daily productivity. The various charts produced by OX Zion identified the peaks and valleys of daily production. When the client was presented with the daily details the department managers offered several explanations for the peaks and valleys. Not surprisingly, reasons were often described as random exceptions – employee absences, scheduled production shutdowns, power outages, etc. – and not a predictable, manageable pattern.

To prove the drops in production were no exceptions but the rule, Vantage Agora took a much more basic approach to data visualization: we plotted the data on a calendar.

The results were obvious, the staff simply didn’t have productive days on Thursdays and Fridays. The colors represent whether the daily production Met/Exceeded Expectations (green), Missed Production Expectations (yellow), and Did Not Meet Minimum Thresholds (Red). As this client was approaching their peak season it was essential for the executive team to make changes to their staffing and management model to ensure the staff and team leaders didn’t continue to throttle down their productivity on Thursdays and Fridays when consistently high production was required to meet the market demand.

EXAMPLE 2

The same client then wanted to reward their highest performers and was basing those decisions on the recommendations of the team leaders and department managers. What was evident in the process was no one took a global approach to overall productivity because a high performer in one department does not always measure up to the high performers in other departments.

Vantage Agora delivered data visualization by compiling the Big Data from multiple sources. By measuring all the production employees across similar metrics and cross referencing that data to time sheets we could identify not only the high producers but also the most efficient employees. In this example, Employee 1 and Employee 2 were ranked as high performers in different departments and each were scheduled for a high performer bonus.

The on-demand data visualization provided by Vantage Agora’s OX Zion determined that Employee 1 and Employee 2 were not equally productive in any way. Employee 1 was a high performer as measured by throughput but the analysis also determined a high level of efficiency. Employee 1 could achieve the high-performance levels within an 8-hour day, whereas Employee 2 achieved above average performance levels but at a rate of an 8-hour day plus an average of 2.5 hours of overtime each day.

When the management team realized Employee 1 was a high performer as well as incredibly efficient during an 8-hour day that employee was rewarded above all others. Additionally, the perception of Employee 2 changed from a high performer to a below average performer because the production numbers were dependent on an average of 12.5 hours of overtime each week.

When all the available Big Data was included in the side-by-side comparison of Employee 1 and Employee 2 it became evident who was the most valuable employee. At the beginning of the exercise Employee 1 and Employee 2 were viewed as peers, but the analysis showed Employee 2 produced LESS THAN HALF the volume of Employee 1 at a greater cost due to the overtime. Additionally, other employees who were not previously viewed as high performers were now targeted for additional development opportunities and employee recognition.

To see how your company – and your high performing employees – can benefit from on-demand data visualization with OX Zion, contact us today!

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